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Multi-user massive MIMO channel estimation method based on Bayesian method

A channel estimation, multi-user technology, applied in the field of channel estimation of multi-user massive MIMO systems, can solve problems such as large training overhead, meaningless channel estimation, and longer training time, and achieve the effect of reducing overhead

Inactive Publication Date: 2015-12-02
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

In this case, the number of pilot signals is proportional to the number of base station antennas. Due to the huge number of antennas in massive MIMO systems, conventional channel estimation methods (such as the least squares method) will face huge training overhead, making the training time become shorter. Long, even exceeding the channel's dry time, making channel estimation meaningless

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  • Multi-user massive MIMO channel estimation method based on Bayesian method
  • Multi-user massive MIMO channel estimation method based on Bayesian method
  • Multi-user massive MIMO channel estimation method based on Bayesian method

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Embodiment Construction

[0036] The technical solution of the present invention will be described in detail below in combination with the embodiments and the accompanying drawings.

[0037] figure 1 A schematic diagram of a multi-user massive MIMO channel.

[0038] Assuming that the number of users is K=30, the base station and the user end are each equipped with a uniform linear array (ULA), and the number of antennas of the base station is N=150, and the number of antennas of each user is the same and M=2. Assuming that the sparse support number (sparse degree) of each user channel is the same and s=15, the common sparse support number s c =7.

[0039] figure 2It is a flow chart of multi-user massive MIMO channel estimation. According to the flow chart, the above parameters can be used to simulate the algorithm.

[0040] S1. Initialization, specifically:

[0041] S11, BS uses T time slots to broadcast T pilot signals to K MSs X=[x (1) ,x (2) ,...,x (T) ]∈C N×T , where N is the number of an...

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Abstract

The invention belongs to the technical field of wireless communication, and specifically relates to a channel estimation method for a multi-user massive MIMO (MU-Massive MIMO) system in the frequency division duplex (FDD) mode. In the multi-user massive MIMO system, according to the method, the combined sparsity of the channel is employed, a sparse signal reconstruction algorithm based on the Bayesian method is introduced to perform channel estimation, the expense of channel estimation is greatly reduced, the channel estimation time is far less than the channel coherence time, the expense of channel estimation is reduced to 20% of the expense by employing a conventional channel estimation method, the channel estimation time is far less than the channel coherence time, and the realization of the massive MIMO channel estimation is possible in reality.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, and in particular relates to a channel estimation method of a multi-user massive MIMO (MU-Massive MIMO) system in a frequency division duplex (FDD) mode. Background technique [0002] The massive MIMO system is one of the key technologies of the fifth-generation mobile communication system. Its main advantages are: the system capacity increases with the number of antennas; the transmission signal power is reduced; the simple linear precoder and detector can achieve the maximum Excellent performance; the channels tend to be orthogonal, thus eliminating co-channel interference in the cell. The prerequisite for realizing these advantages is that the base station (BS) knows the channel state information (CSIT). In a Time Division Duplex (TDD) system, channel estimation is performed at the user end (MS) by utilizing the reciprocity of the uplink and downlink channels. Then the channel...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L25/02
Inventor 付自刚成先涛
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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